Advanced International Journal for Research

E-ISSN: 3048-7641   •   Impact Factor: 9.11

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Volume 6 Issue 6
November-December 2025

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Building Conversation Agent using Sign Language

Author(s) Mr. SERVESH JAIMANGAL GUPTA, Mr. PRATIK TAWDE
Country India
Abstract This paper uses a synergistic strategy that blends deep learning and advanced computer vision techniques to propose a revolutionary implementation of real-time alphabet and hand gesture recognition to give both text and speech results with high accuracy. Utilizing cutting-edge Python modules like Mediapipe, OpenCV, and TensorFlow, in this paper they record, interpret, and recognize hand gestures and words from a camera feed in real-time effectively. This paper implements the use of advanced technological models such as YOLOv7 along with NLPs such as TTS (Text to Speech) to provide improved results. By utilizing syntax techniques that involves breaking down the text into smaller components, such as words or phrases, and then using algorithms to identify patterns in the data. After identification, they can be used to generate output, such as a text-to-speech model or lifelike voices. YOLOv7 also shows faster inference speed and better detection accuracy. To improve the system's usability and engagement, further capabilities include robust landmark gathering, data processing, visualization approaches, and post-recognition result processing. It is a significant development in the accessibility and interaction technology arena because of its potential uses in a variety of fields, including as sign language interpretation, human-computer interaction, and the creation of interactive user interfaces.
Keywords NLP, Gesture Detection, CNN, TTS, Sign Language
Field Engineering
Published In Volume 6, Issue 6, November-December 2025
Published On 2025-12-11
DOI https://doi.org/10.63363/aijfr.2025.v06i06.2334
Short DOI https://doi.org/hbf95m
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